Calculating and Characterizing the Charge Distributions in Solids

Efficient treatment of long-range electrostatics in charge equilibration approaches

A charge equilibration method based on real-space Gaussians as charge densities is presented. The implementation is part of the Electrode package available in the Large-scale Atomic/Molecular Massively Parallel Simulator and benefits from its efficient particle-mesh Ewald approach. A simple strategy required to switch from the previously used Slater-type orbital (STO) shielding to Gaussians is provided by fitting the Coulomb energy of two Gaussian charge distributions to the repulsion between two STOs. Their widths were optimized for O, Si, and Ti species, obtaining results consistent with previous studies using STOs in the case of SiO2 polymorphs. In the limit of sufficiently narrow Gaussians, it is shown that the implementation converges to electronegativity equalization method results for the case of Ti/TiOx interfaces. The method presented is implemented in a way that is potentially beneficial for the application of modern machine-learning force fields that include long-range electrostatic interactions.

Layered ion dynamics and enhanced energy storage: VS2/MXene heterostructure anodes revolutionizing Li-ion batteries

Two-dimensional (2D) material-based anodes are pivotal for advancing next-generation ion batteries, showing remarkable ion loading capacity and mobility. In this intricate study, we employed first-principles calculations to delve into the five-layer lithium ion (Li-ion) loading on transition-metal dichalcogenide (TMD; specifically VS2) paired with MXene (Ti3C2O2 and V3C2O2) heterostructures. Our investigation meticulously assessed adsorption sites, binding energies, and charge transfers. Using sophisticated first-principles calculations, we probed into the Li-ion intercalation process, meticulously determining open-circuit voltages (OCV), which intriguingly ranged from 3.14 to 1.30 V for VS2/Ti3C2O2 and 2.60 to 0.73 V for VS2/V3C2O2. The adsorption energies (Ead) were equally fascinating, with values of -2.86 eV per Li-ion for VS2/Ti3C2O2 and -2.65 eV per Li-ion for VS2/V3C2O2. The optimized VS2/Ti3C2O2 heterostructure demonstrated a staggering Li storage capacity of 425.84 mA h g-1. Not far behind, the VS2/V3C2O2 heterostructure exhibited a notable Li storage capacity of 413.19 mA h g-1, surpassing previously reported 2D anode materials. Following this, ab initio molecular dynamics (AIMD) simulations exposed significant variations within the VS2/Ti3C2O2 and VS2/V3C2O2 heterostructures. These simulations suggest that both the VS2/Ti3C2O2 and VS2/V3C2O2 heterostructures are not only promising, but also highly efficient anode materials for the realization of sustainable Li-ion batteries.

Workflow-driven catalytic modulation from single-atom catalysts to Au-alloy clusters on graphene

Gold-based (Au) nanostructures are efficient catalysts for CO oxidation, hydrogen evolution (HER), and oxygen evolution (OER) reactions, but stabilizing them on graphene (Gr) is challenging due to weak affinity from delocalized [Formula: see text] carbon orbitals. This study investigates forming metal alloys to enhance stability and catalytic performance of Au-based nanocatalysts. Using ab initio density functional theory, we characterize [Formula: see text] sub-nanoclusters (M = Ni, Pd, Pt, Cu, and Ag) with atomicities [Formula: see text], both in gas-phase and supported on Gr. We find that M atoms act as "anchors," enhancing binding to Gr and modulating catalytic efficiency. Notably, [Formula: see text]/Gr shows improved stability, with segregation tendencies mitigated upon adsorption on Gr. The d-band center ([Formula: see text]) model indicates catalytic potential, correlating an optimal [Formula: see text] range of [Formula: see text] eV for HER and OER catalysts. Incorporating Au into [Formula: see text] adjusts [Formula: see text] closer to the Fermi level, especially for Group-10 alloys, offering designs with improved stability and efficiency comparable to pure Au nanocatalysts. Our methodology leveraged SimStack, a workflow framework enabling modeling and analysis, enhancing reproducibility, and accelerating discovery. This work demonstrates SimStack's pivotal role in advancing the understanding of composition-dependent stability and catalytic properties of Au-alloy clusters, providing a systematic approach to optimize metal-support interactions in catalytic applications.

In silico characterization of nanoparticles

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.

Triazole based Schiff bases and their Oxovanadium(IV) complexes: Synthesis, characterization, antibacterial assay, and computational assessments

The synthesis and characterization of two new Schiff base ligands containing 1,2,4-triazole moieties and their oxovanadium(IV) complexes have been reported. The ligands and their complexes were studied by ultraviolet-visible (UV-Vis), Fourier transform infrared (FTIR), proton nuclear magnetic resonance (¹H NMR), electron paramagnetic resonance (EPR), X-ray diffraction (XRD), conductivity measurement, cyclic voltammetry (CV), and elemental analyses. The molar conductance of oxovanadium(IV) complexes were found to be relatively low, depicting their non-electrolytic nature. The XRD patterns reveal the size of particles to be 47.53 nm and 26.28 nm for the two complexes in the monoclinic crystal system. The molecular structures, geometrical parameters, chemical reactivity, stability, and frontier molecular orbital pictures were determined by density functional theory (DFT) calculations. The theoretical vibrational frequencies and EPR g-factors (1.98) were found to correlate well with the experimental values. A distorted square pyramidal geometry with C₂ symmetry of the complexes has been proposed from experimental and theoretical results in a synergistic manner. The antimicrobial sensitivity of the ligands and their metal complexes assayed in vitro against four bacterial pathogens viz. Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Salmonella Typhi showed that the oxovanadium(IV) complexes are slightly stronger antibacterial agents than their corresponding Schiff base precursors. The binding affinities obtained from the molecular docking calculations with the receptor proteins of bacterial strains (2EUG, 3UWZ, 4GVF, and 4JVD) showed that the Schiff bases and their oxovanadium(IV) complexes have considerable capacity inferring activeness for effective inhibition. The molecular dynamics simulation of a protein-ligand (4JVD-HL₂) complex with the best binding affinity of -12.8 kcal/mol for 100 ns showed acceptable stability of the docked pose and binding free energy of -15.17 ± 2.29 kcal/mol from molecular mechanics-generalized Born surface area (MM-GBSA) calculations indicated spontaneity of the reaction. The outcome of the research shows the complementary role of computational methods in material characterization and provides an interesting avenue to pursue for exploring new triazole based Schiff's bases and its vanadium compounds for better properties.

Anab initiostudy of catechol sensing in pristine and transition metal decoratedγ-graphyne

Catechol is a toxic biomolecule due to its low degradability to the ecosystem and unpredictable impact on human health. In this work, we have investigated the catechol sensing properties of pristine and transition metal (Ag, Au, Pd, and Ti) decoratedγ-graphyne (GY) systems by employing the density functional theory and first-principles molecular dynamics approach. Simulation results revealed that Pd and Ti atom is more suitable than Ag and Au atom for the decoration of the GY structure with a large charge transfer of 0.29e and 1.54e from valence d-orbitals of the Pd/Ti atom to the carbon-2p orbitals of GY. The GY + Ti system offers excellent electrochemical sensing towards catechol with charge donation of 0.14e from catechol O-p orbitals to Ti-d orbitals, while the catechol molecule is physisorbed to pristine GY with only 0.04e of charge transfer. There exists an energy barrier of 5.19 eV for the diffusion of the Ti atom, which prevents the system from metal-metal clustering. To verify the thermal stability of the sensing material, we have conducted the molecular dynamics simulations at 300 K. We have reported feasible recovery times of 2.05 × 10^-5s and 4.7 × 10²s for sensing substrate GY + Pd and GY + Ti, respectively, at 500 K of UV light.

Atomistic insight into the effects of electrostatic fields on hydrocarbon reaction kinetics

Reactive Molecular Dynamics (MD) and Density Functional Theory (DFT) computations are performed to provide insight into the effects of external electrostatic fields on hydrocarbon reaction kinetics. By comparing the results from MD and DFT, the suitability of the MD method in modeling electrodynamics is first assessed. Results show that the electric field-induced polarization predicted by the MD charge equilibration method is in good agreement with various DFT charge partitioning schemes. Then, the effects of oriented external electric fields on the transition pathways of non-redox reactions are investigated. Results on the minimum energy path suggest that electric fields can cause catalysis or inhibition of oxidation reactions, whereas pyrolysis reactions are not affected due to the weaker electronegativity of the hydrogen and carbon atoms. MD simulations of isolated reactions show that the reaction kinetics is also affected by applied external Lorentz forces and interatomic Coulomb forces since they can increase or decrease the energy of collision depending on the molecular conformation. In addition, electric fields can affect the kinetics of polar species and force them to align in the direction of field lines. These effects are attributed to energy transfer via intermolecular collisions and stabilization under the external Lorentz force. The kinetics of apolar species is not significantly affected mainly due to the weak induced dipole moment even under strong electric fields. The dynamics and reaction rates of species are studied by means of large-scale combustion simulations of n-dodecane and oxygen mixtures. Results show that under strong electric fields, the fuel, oxidizer, and most product molecules experience translational and rotational acceleration mainly due to close charge transfer along with a reduction in their vibrational energy due to stabilization. This study will serve as a basis to improve the current methods used in MD and to develop novel methodologies for the modeling of macroscale reacting flows under external electrostatic fields.

Water Uptake in an Anion Exchange Membrane Based on Polyamine: A First-Principles Study

An atomistic level study of a single monomer of polyamine interacting with water molecules and hydroxide anions (OH^-) was carried out to investigate the role of the polyamine structure in the hydrated morphology of anion exchange membranes (AEMs) for alkaline fuel cells and its influence on ionic conductivity and chemical stability. DFT calculations were performed to find the ground state of the system, studying the interactions of the solvent species with three different regions of the polymer─the amine functional group, the backbone, and the carbonyl group. The hydrophilic/hydrophobic behavior of each segment was determined, with calculated binding energies and Bader charge analysis providing a more quantitative analysis of the interactions and activation and reaction energies computed to investigate the chemical degradation mechanism. The results show the tendency of both OH^- and water molecules to form water clusters in the proximity of the ionized amine group. As such, these regions constitute the preferential pathway for ionic conductivity. Besides, the essential role of the water content is pointed out, not only to enhance conductivity but also to reduce degradation in an alkaline environment. The present work provides a baseline to assess the impact of polymer chemistry on the ionic conductivity of the membrane and acts as the first step for the development of high-performance AEMs and for an improvement of the overall performance of the fuel cell.

Single-Step Mechanism for Regioselective Nitration of 9,10-BN-Napthalene with Acetyl Nitrate in the Gas Phase

The energetics of the regioselective mononitration of 9,10-BN-naphthalene with acetyl nitrate (H₃C₂NO₄) were modeled with ab initio simulations in the gas phase and an acetonitrile solvent. The single-electron-transfer (SET) nitration mechanism leading to a σ-complex and a single-step nitration mechanism were modeled. The energy barrier for the single-step mechanism was lower than that for the SET mechanism in the gas phase. However, the two are much more energetically competitive in the solvent. The σ-complex was found to be unstable in the gas phase owing to the interaction with the counterion. Using the single-step mechanism, the carbon site 1 nearest boron had the lowest activation energy for nitration of 22.6 kcal/mol, while site 3 had the second lowest barrier of 24.6 kcal/mol. Details on the molecular structures at intermediate and transition states as well as charges in different configurations are discussed.

Benchmarking various types of partial atomic charges for classical all-atom simulations of metal-organic frameworks

The density derived electrostatic and chemical (DDEC) approach for calculating the charges of atoms in a metal-organic framework (MOF) is considered to be the most accurate (yet computationally costly) one among many charge-assignment methods. Here, we conducted a comparative study on five different types of atomic partial charges (namely CM5, Mulliken, Qeq, EQeq and PACMOF) prepared for a subset of MOFs with affordable computational costs and benchmarked them with respect to the DDEC charges, which is particularly relevant because currently most databases lack MOFs with pre-calculated DDEC charges. To find a suitable charge type alternative to the DDEC approach, we statistically ranked the five charge types based on two metrics, the relative standard deviation of charges and relative dipole moment difference, based on which we provide general guidance as well as suggestions for specific MOFs according to bond polarity analyses. Finally, we recommend a possible and more accurate parametrization scheme for future studies.

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal-Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal-organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO₂. Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal-Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. A strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

Oxygen adsorption on (100) surfaces in Fe-Cr alloys

The adsorption of oxygen on bcc Fe–Cr(100) surfaces with two different alloy concentrations is studied using ab initio density functional calculations. Atomic-scale analysis of oxygen–surface interactions is indispensable for obtaining a comprehensive understanding of macroscopic surface oxidation processes. Up to two chromium atoms are inserted into the first two surface layers. Atomic geometries, energies and electronic properties are investigated. A hollow site is found to be the preferred adsorption site over bridge and on-top sites. Chromium atoms in the surface and subsurface layers are found to significantly affect the adsorption properties of neighbouring iron atoms. Seventy-one different adsorption geometries are studied, and the corresponding adsorption energies are calculated. Estimates for the main diffusion barriers from the hollow adsorption site are given. Whether the change in the oxygen affinity of iron atoms can be related to the chromium-induced charge transfer between the surface atoms is discussed. The possibility to utilize the presented theoretical results in related experimental research and in developing semiclassical potentials for simulating the oxidation of Fe–Cr alloys is addressed.

Determining Partial Atomic Charges for Liquid Water: Assessing Electronic Structure and Charge Models

Partial atomic charges provide an intuitive and efficient way to describe the charge distribution and the resulting intermolecular electrostatic interactions in liquid water. Many charge models exist and it is unclear which model provides the best assignment of partial atomic charges in response to the local molecular environment. In this work, we systematically scrutinize various electronic structure methods and charge models (Mulliken, natural population analysis, CHelpG, RESP, Hirshfeld, Iterative Hirshfeld, and Bader) by evaluating their performance in predicting the dipole moments of isolated water, water clusters, and liquid water as well as charge transfer in the water dimer and liquid water. Although none of the seven charge models is capable of fully capturing the dipole moment increase from isolated water (1.85 D) to liquid water (about 2.9 D), the Iterative Hirshfeld method performs best for liquid water, reproducing its experimental average molecular dipole moment, yielding a reasonable amount of intermolecular charge transfer, and showing modest sensitivity to the local water environment. The performance of the charge model is dependent on the choice of the density functional and the quantum treatment of the environment. The computed molecular dipole moment of water generally increases with the percentage of the exact Hartree-Fock exchange in the functional, whereas the amount of charge transfer between molecules decreases. For liquid water, including two full solvation shells of surrounding water molecules (within about 5.5 Å of the central water) in the quantum chemical calculation converges the charges of the central water molecule. Our final pragmatic quantum chemical charge-assigning protocol for liquid water is the Iterative Hirshfeld method with M06-HF/aug-cc-pVDZ and a quantum region cutoff radius of 5.5 Å.